16433 Zip Code Historical Amount of Rooms in a House Data
ACS 2010-2014 data
| 16433 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 2,443, 100% | 5,578,393 | 132,741,033 |
1 Room | 2, 0.08%, see rank | 1.73% | 1.95% |
2 Rooms | 20, 0.82%, see rank | 1.73% | 2.48% |
3 Rooms | 140, 5.73%, see rank | 7.21% | 9.13% |
4 Rooms | 278, 11.38%, see rank | 12.40% | 16.60% |
5 Rooms | 596, 24.40%, see rank | 16.40% | 20.41% |
6 Rooms | 569, 23.29%, see rank | 21.82% | 18.06% |
7 Rooms | 373, 15.27%, see rank | 14.82% | 12.27% |
8 Rooms | 223, 9.13%, see rank | 10.70% | 8.48% |
9 Rooms or More | 242, 9.91%, see rank | 13.18% | 10.60% |
Median Rooms | 5.80, see rank | 6.00 | 5.50 |
ACS 2008-2012 data
| 16433 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 2,355, 100% | 5,563,832 | 131,642,457 |
1 Room | 20, 0.85%, see rank | 1.68% | 1.95% |
2 Rooms | 19, 0.81%, see rank | 1.69% | 2.36% |
3 Rooms | 140, 5.94%, see rank | 7.15% | 8.97% |
4 Rooms | 281, 11.93%, see rank | 12.46% | 16.57% |
5 Rooms | 567, 24.08%, see rank | 16.43% | 20.41% |
6 Rooms | 571, 24.25%, see rank | 21.86% | 18.25% |
7 Rooms | 323, 13.72%, see rank | 14.93% | 12.38% |
8 Rooms | 257, 10.91%, see rank | 10.77% | 8.59% |
9 Rooms or More | 177, 7.52%, see rank | 13.03% | 10.52% |
Median Rooms | 5.80, see rank | 6.00 | 5.50 |
US Census 2000 data
| 16433 Zip Code | Pennsylvania | U.S. |
Total Housing Units | 2,125, 100% | 5,249,750 | 115,904,641 |
1 Room | 19, 0.89%, see rank | 1.19% | 2.20% |
2 Rooms | 32, 1.51%, see rank | 2.73% | 4.81% |
3 Rooms | 60, 2.82%, see rank | 7.69% | 9.84% |
4 Rooms | 322, 15.15%, see rank | 12.73% | 15.97% |
5 Rooms | 495, 23.29%, see rank | 17.61% | 20.89% |
6 Rooms | 496, 23.34%, see rank | 23.25% | 18.45% |
7 Rooms | 323, 15.20%, see rank | 14.62% | 12.06% |
8 Rooms | 199, 9.36%, see rank | 10.69% | 8.06% |
9 Rooms or More | 179, 8.42%, see rank | 9.49% | 7.70% |
Median Rooms | 5.80, see rank | 5.80 | 5.30 |
* ACS stands for U.S. Census American Community Survey. According to the U.S. Census, if the date is a range, you can interpret the data as an average of the period of time.